A bioinformatics approach to identifying potential biomarkers for Cryptosporidium parvum: A coccidian parasite associated with fetal diarrhea

Sabir, Mumdooh J., Low, Ross, Hall, Neil, Kamli, Majid Rasool and Malik, Md. Zubbair (2021) A bioinformatics approach to identifying potential biomarkers for Cryptosporidium parvum: A coccidian parasite associated with fetal diarrhea. Vaccines, 9 (12). ISSN 2076-393X

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Abstract

Cryptosporidium parvum (C. parvum) is a protozoan parasite known for cryptosporidiosis in pre-weaned calves. Animals and patients with immunosuppression are at risk of developing the disease, which can cause potentially fatal diarrhoea. The present study aimed to construct a network biology framework based on the differentially expressed genes (DEGs) of C. parvum infected subjects. In this way, the gene expression profiling analysis of C. parvum infected individuals can give us a snapshot of actively expressed genes and transcripts under infection conditions. In the present study, we have analyzed microarray data sets and compared the gene expression profiles of the patients with the different data sets of the healthy control. Using a network medicine approach to identify the most influential genes in the gene interaction network, we uncovered essential genes and pathways related to C. parvum infection. We identified 164 differentially expressed genes (109 up- and 54 down-regulated DEGs) and allocated them to pathway and gene set enrichment analysis. The results underpin the identification of seven significant hub genes with high centrality values: ISG15, MX1, IFI44L, STAT1, IFIT1, OAS1, IFIT3, RSAD2, IFITM1, and IFI44. These genes are associated with diverse biological processes not limited to host interaction, type 1 interferon production, or response to IL-gamma. Furthermore, four genes (IFI44, IFIT3, IFITM1, and MX1) were also discovered to be involved in innate immunity, inflammation, apoptosis, phosphorylation, cell proliferation, and cell signaling. In conclusion, these results reinforce the development and implementation of tools based on gene profiles to identify and treat Cryptosporidium parvum-related diseases at an early stage.

Item Type: Article
Uncontrolled Keywords: sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Faculty of Science > School of Biological Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 10 Dec 2021 11:31
Last Modified: 30 May 2022 16:31
URI: https://ueaeprints.uea.ac.uk/id/eprint/82632
DOI: 10.3390/vaccines9121427

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